Data & Analytics Product Owner - Azure & AI

Stena Metall AB

Göteborgs kommun

On-site

SEK 700,000 - 1,000,000

Full time

4 days ago
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Job summary

Stena Recycling Group is seeking an experienced Product Owner with a strong Data & Analytics background to lead a portfolio of analytics capabilities. You will collaborate with Data Engineers, BI Developers, Information Architects and Solution Architects to turn business needs into valuable digital solutions.

You will define product vision, roadmap and OKRs with management, prioritise backlogs by value and feasibility, and drive AI-enabled opportunities to enhance decision making and business

Qualifications

  • Bachelor's degree in computer science, engineering or related field.
  • At least 5 years of Data & Analytics experience.
  • Experience with cloud data platforms, data lake and data warehousing.
  • Fluent in Swedish and English.

Responsibilities

  • Define product vision, roadmap and OKRs with management.
  • Translate business needs into product outcomes, capabilities and features.
  • Manage and prioritize product backlogs by value, impact and feasibility.
  • Empower the product team with context, direction, and priorities.
  • Drive stakeholder alignment across business, technology and management.
  • Promote knowledge sharing, reuse and synergies across products.
  • Explore how AI can create new opportunities and business value.

Skills

Product ownership
Data & Analytics
Agile methodologies
Stakeholder management
Cloud data platforms
AI opportunities

Education

Bachelor's degree in computer science, engineering or related field

Tools

Azure
Qlik
Dynamics 365

Job description

Stena Recycling Group is seeking an experienced Product Owner with a strong Data & Analytics background to lead a portfolio of analytics capabilities. You will collaborate with Data Engineers, BI Developers, Information Architects and Solution Architects to turn business needs into valuable digital solutions.

You will define product vision, roadmap and OKRs with management, prioritise backlogs by value and feasibility, and drive AI-enabled opportunities to enhance decision making and business

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